View source: R/F_plotRespFun.R
plotRespFun | R Documentation |
Plots a number of response functions over the observed range of the environmental score. If no taxa are provided those who react most strongly to the environmental score are chosen.
plotRespFun(
RCM,
taxa = NULL,
type = "link",
logTransformYAxis = FALSE,
addSamples = TRUE,
samSize = NULL,
Dim = 1L,
nPoints = 100L,
labSize = 2.5,
yLocVar = NULL,
yLocSam = NULL,
Palette = "Set3",
addJitter = FALSE,
nTaxa = 9L,
angle = 90,
legendLabSize = 15,
legendTitleSize = 16,
axisLabSize = 14,
axisTitleSize = 16,
lineSize = 0.75,
...
)
RCM |
an RCM object |
taxa |
a character vector of taxa to be plotted |
type |
a character string, plot the response function on the log-scale ('link') or the abundance scale 'response', similar to predict.glm(). |
logTransformYAxis |
a boolean, should y-axis be log transformed? |
addSamples |
a boolean, should sample points be shown? |
samSize |
a sample variable name or a vector of length equal to the number of samples, for the sample sizes |
Dim |
An integer, the dimension to be plotted |
nPoints |
the number of points to be used to plot the lines |
labSize |
the label size for the variables |
yLocVar |
the y-location of the variables, recycled if necessary |
yLocSam |
the y-location of the samples, recycled if necessary |
Palette |
which color palette to use |
addJitter |
A boolean, should variable names be jittered to make them more readable |
nTaxa |
an integer, number of taxa to plot |
angle |
angle at which variable labels should be turned |
legendLabSize |
size of the legend labels |
legendTitleSize |
size of the legend title |
axisLabSize |
size of the axis labels |
axisTitleSize |
size of the axis title |
lineSize |
size of the response function lines |
... |
Other argumens passed on to the ggplot() function |
Plots a ggplot2-object to output
RCM
, plot.RCM
,residualPlot
data(Zeller)
require(phyloseq)
tmpPhy = prune_taxa(taxa_names(Zeller)[1:100],
prune_samples(sample_names(Zeller)[1:50], Zeller))
#Subset for a quick fit
zellerRCMnp = RCM(tmpPhy, k = 2,
covariates = c('BMI','Age','Country','Diagnosis','Gender'),
round = TRUE, responseFun = 'nonparametric')
plotRespFun(zellerRCMnp)
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